A conventional way to measure nervous system function is to record an evoked potential (EP) in response to a stimulus which is often presented repeatedly. The EP is a voltage representing the summed electrical activity of large number of neurones that reside near the recording electrodes. More recently, measurement of stimulus evoked responses (SERs) such as changes in magnetic fields or optical signals generated by neural activity have come into use. Another response generated by the nervous system providing possible utility is the pupillary response. Similarly the electroculogram, or eye movements measured in other ways, could be used. Such non-invasive measurement is desirable in the clinical setting and so neural activity is typically recorded from or through the skin in what might be described as surface recording. For example, evoked electrical potentials reflecting brain activity are easily recorded from electrodes placed upon the scalp. Magnetic and infrared signals related to neural activity can be similarly recorded through the skin. A potential drawback of surface measurements, or eye movements, or the pupillary response is that, however they are measured, these evoked responses typically represent the summed activity of many neurones in response to the stimulus.
Diseases affecting the nervous system may impact upon sections of the nervous system differentially. For example in the eye disease glaucoma separate parts of the retina are differentially affected causing localised reduction of visual performance in particular parts of the visual field. Like multiple sclerosis the damage caused by the disease is localised to small regions along the nerves and neural pathways within the brain. Thus, in such cases it would be useful to test neural function with multiple stimuli at the same time, each stimulus testing a different section of the nervous system, in what might be called Multi-stimulus Evoked Responses (MSERs). Measurement of MSERs to some extent minimises the difficulties of recording evoked responses. So, for example, stimuli presented to multiple parts of the visual field at the same time would in principle allow efficient mapping of the visual field even with a single recording sensor placed on or near the eye or scalp. Thus, the problems of recording evoked responses are reduced when responses to stimuli to multiple parts of the nervous system can be recorded.
While some MSER methods have been proposed, the emphasis in the design of the stimulus sequences used to date has been to reduce the computational burden in estimating the responses and/or to reduce the degree of correlation between the stimulus sequences. For example, Wiener, N (“Nonlinear problems in random theory”, New York, Wiley, 1958) proposed the use of continuous Gaussian distributed white noise as a stimulus sequence that in principle could be used for MSERs. More recently Sutter, E (U.S. Pat. No. 4,846,567) proposed the use of special stimulus sequences called m-sequences where the stimulus sequence fluctuates between one of two levels in a strictly defined way. These two level m-sequences are a subset of a class of sequences that are said to be binary. These binary sequences vary between two about equally likely stimulus conditions and thus, unlike the stimuli proposed hereinafter, never contain a null condition and are not sparse in the sense presented herein. Neither of the stimuli of Wiener or Sutter is designed to optimise responses from any particular part of the nervous system. Stimuli that permit the measurement of MSERs but which are optimised for assessing clinically relevant parts of the nervous system would be potentially more useful.
Of particular interest in assessment of neural function may be those parts of the nervous system that dynamically adapt to prevailing stimulus conditions by using so called gain control mechanisms. These neural systems are interesting from the point of view of studying neural performance because these gain control systems are often complex and strictly controlled. Thus, neural dysfunction might be readily observed in neural systems exhibiting gain control mechanisms. At the same time appropriate design of stimulus sequences might permit neural systems with gain control systems to produce larger and or more reliable responses.